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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11

Modeling the Impact of Grain Size on Corrosion Behavior of Ni-Based Alloys in Molten Chloride Salt via Cellular Automata

Molten chloride salts hold significant promise as both thermal transfer and storage media for next-generation concentrated solar power (CSP) systems. However, molten chlorides pose a considerable corrosion risk to structural materials, particularly Ni-based alloys. One approach to enhancing corrosion resistance is through the optimization of grain structure; however, it remains uncertain whether increasing or decreasing grain size enhances corrosion resistance. A cellular automata (CA) program was developed to evaluate the interplay between grain size and corrosion in Ni-based alloy. Our CA program tracks alloy composition, surface roughness, and thickness loss via a graphical user interface, displaying corrosion and diffusion status, and multiple user input cards for tuning the simulation. CA simulations of Inconel 625 indicate enhanced corrosion resistance with increased grain size, with passivating oxides offering limited protection. Additionally, the temporal evolution of alloy surface roughness demonstrates notable fluctuations, with abrupt increases attributed to corrosion along vertical grain boundaries and sudden decreases to grain detachment from the protective film.

Materials Science↗

Recovering the Star Formation Histories of Recently Quenched Galaxies: The Impact of Model and Prior Choices

Accurate models of the star formation histories (SFHs) of recently quenched galaxies can provide constraints on when and how galaxies shut down their star formation. The recent development of nonparametric SFH models promises the flexibility required to make these measurements. However, model and prior choices significantly affect derived SFHs, particularly for post-starburst galaxies (PSBs), which have sharp changes in their recent SFH. In this paper, we create mock PSBs, then use the Prospector SED fitting software to test how well four different SFH models recover key properties. We find that a two-component parametric model performs well for our simple mock galaxies, but is sensitive to model mismatches. The fixed- and flexible-bin nonparametric models included in Prospector are able to rapidly quench a major burst of star formation, but systematically underestimate the post-burst age by up to 200 Myr. We develop a custom SFH model that allows for additional flexibility in the recent SFH. Our flexible nonparametric model is able to constrain post-burst ages with no significant offset and just ~90 Myr of scatter. Our results suggest that while standard nonparametric models are able to recover first-order quantities of the SFH (mass, SFR, average age), accurately recovering higher-order quantities (burst fraction, quenching time) requires careful consideration of model flexibility. These mock recovery tests are a critical part of future SFH studies. Finally, we show that our new, public SFH model is able to accurately recover the properties of mock star-forming and quiescent galaxies and is suitable for broader use in the SED fitting community. https://github.com/bd-j/prospector

79 ASTRONOMY AND ASTROPHYSICS↗

Lunar crater volumes - Interpretation by models of impact cratering and upper crustal structure

Lunar crater volumes can be divided by size into two general classes with distinctly different functional dependence on diameter. Craters smaller than approximately 12 km in diameter are morphologically simple and increase in volume as the cube of the diameter, while craters larger than about 20 km are complex and increase in volume at a significantly lower rate implying shallowing. Ejecta and interior volumes are not identical and their ratio, Schroeters Ratio (SR), increases from about 0.5 for simple craters to about 1.5 for complex craters. The excess of ejecta volume causing the increase, can be accounted for by a discontinuity in lunar crust porosity at 1.5-2 km depth. The diameter range of significant increase in SR corresponds with the diameter range of transition from simple to complex crater morphology. This observation, combined with theoretical rebound calculation, indicates control of the transition diameter by the porosity structure of the upper crust.

Croft, S. K.↗

Yearly variations of rain-rate statistics at Wallops Island and their impact on modeled slant path attenuation distributions

Rain gauge measurements at Wallops Island, VA over a five-year period have been reduced and cumulative rain-date distributions have been determined for yearly, successively combined years, and overall average cases. Yearly variations of the predicted slant path attenuation statistics for two International Radio Consultative Committee (CCIR) models (referred to as modified method I and method II) and the global model at 28.56 GHz were calculated using the yearly measured rain rates at Wallops Island. This frequency was selected as it coincided with the beacon frequency of te COMSTAR geostationary satellite which was also simultaneously monitored at Wallops Island for a period of three years enabling a comparison with the measured rain-fade statistics. The year to year variations of the predicted fades as well as the percent deviations relative to the five-year average case were examined.

Goldhirsh, J.↗

Assessing the impact of modeling limits on intelligent systems

The knowledge bases underlying intelligent systems are validated. A general conceptual framework is provided for considering the roles in intelligent systems of models of physical, behavioral, and operational phenomena. A methodology is described for identifying limits in particular intelligent systems, and the use of the methodology is illustrated via an experimental evaluation of the pilot-vehicle interface within the Pilot's Associate. The requirements and functionality are outlined for a computer based knowledge engineering environment which would embody the approach advocated and illustrated in earlier discussions. Issues considered include the specific benefits of this functionality, the potential breadth of applicability, and technical feasibility.

Rouse, William B.↗

Assessing the impact of modeling limits on intelligent systems

The knowledge bases underlying intelligent systems are validated. A general conceptual framework is provided for considering the roles in intelligent systems of models of physical, behavioral, and operational phenomena. A methodology is described for identifing limits in particular intelligent systems, and the use of the methodology is illustrated via an experimental evaluation of the pilot-vehicle interface within the Pilot's Associate. The requirements and functionality are outlined for a computer based knowledge engineering environment which would embody the approach advocated and illustrated in earlier discussions. Issues considered include the specific benefits of this functionality, the potential breadth of applicability, and technical feasibility.

Rouse, William B.↗

Photodissociation of O2 and H2O in the middle atmosphere: Comparison of numerical methods and impact on model O3 and OH

We have compared three photochemical diurnal models of O3 and OH in the upper stratosphere and mesosphere which use different techniques for calculating the absorption of solar ultraviolet radiation by the O2 Schumann-Runge bands. One model uses a detailed line-by-line representation of the O2 cross section from 1750-2050 A, while the two others use lower resolution, parameterized cross sections. Using the parameterized cross sections, the calculated O3 profiles for both day and night agree with those obtained from the line-by-line model to within 6%. This appears to eliminate inaccuracies in the parameterized O2 cross section as a major cause of previously reported model O3 deficits. A portion of the residual differences from the line-by-line model are attributed to inaccuracies in the calculated H2O photolysis rate. A parameterized H2O cross section is offered which improves the accuracy of this calculation.

Siskind, David E.↗

Impact of Model Uncertainties on Quantitative Analysis of FUV Auroral Images: Peak Production Height

We demonstrate that small uncertainties in the modeled height of peak production for FUV emissions can lead to significant uncertainties in the analysis of these sai-ne emissions. In particular, an uncertainty of only 3 km in the peak production height can lead to a 50% uncertainty in the mean auroral energy deduced from the images. This altitude uncertainty is comparable to differences in different auroral deposition models currently used for UVI analysis. Consequently, great care must be taken in quantitative photometric analysis and interpretation of FUV auroral images.

Germany, G. A.↗

Modeling the Impact of Drizzle and 3D Cloud Structure on Remote Sensing of Effective Radius

Remote sensing of cloud particle size with passive sensors like MODIS is an important tool for cloud microphysical studies. As a measure of the radiatively relevant droplet size, effective radius can be retrieved with different combinations of visible through shortwave infrared channels. MODIS observations sometimes show significantly larger effective radii in marine boundary layer cloud fields derived from the 1.6 and 2.1 pm channel observations than for 3.7 pm retrievals. Possible explanations range from 3D radiative transport effects and sub-pixel cloud inhomogeneity to the impact of drizzle formation on the droplet distribution. To investigate the potential influence of these factors, we use LES boundary layer cloud simulations in combination with 3D Monte Carlo simulations of MODIS observations. LES simulations of warm cloud spectral microphysics for cases of marine stratus and broken stratocumulus, each for two different values of cloud condensation nuclei density, produce cloud structures comprising droplet size distributions with and without drizzle size drops. In this study, synthetic MODIS observations generated from 3D radiative transport simulations that consider the full droplet size distribution will be generated for each scene. The operational MODIS effective radius retrievals will then be applied to the simulated reflectances and the results compared with the LES microphysics.

Platnick, Steven↗

The Impact of Model and Rainfall Forcing Errors on Characterizing Soil Moisture Uncertainty in Land Surface Modeling

The contribution of rainfall forcing errors relative to model (structural and parameter) uncertainty in the prediction of soil moisture is investigated by integrating the NASA Catchment Land Surface Model (CLSM), forced with hydro-meteorological data, in the Oklahoma region. Rainfall-forcing uncertainty is introduced using a stochastic error model that generates ensemble rainfall fields from satellite rainfall products. The ensemble satellite rain fields are propagated through CLSM to produce soil moisture ensembles. Errors in CLSM are modeled with two different approaches: either by perturbing model parameters (representing model parameter uncertainty) or by adding randomly generated noise (representing model structure and parameter uncertainty) to the model prognostic variables. Our findings highlight that the method currently used in the NASA GEOS-5 Land Data Assimilation System to perturb CLSM variables poorly describes the uncertainty in the predicted soil moisture, even when combined with rainfall model perturbations. On the other hand, by adding model parameter perturbations to rainfall forcing perturbations, a better characterization of uncertainty in soil moisture simulations is observed. Specifically, an analysis of the rank histograms shows that the most consistent ensemble of soil moisture is obtained by combining rainfall and model parameter perturbations. When rainfall forcing and model prognostic perturbations are added, the rank histogram shows a U-shape at the domain average scale, which corresponds to a lack of variability in the forecast ensemble. The more accurate estimation of the soil moisture prediction uncertainty obtained by combining rainfall and parameter perturbations is encouraging for the application of this approach in ensemble data assimilation systems.

Maggioni, V.↗